{
  "model_name": "WoFS-StormCal",
  "model_type": "wofsstormcal",
  "architectures": ["WoFSStormCal"],
  "framework": "PyTorch",
  "domain": "meteorology",
  "task": "storm-object-multilabel-severe-hazard-probability",
  "license": "Apache-2.0",
  "implementation": {
    "entry_point": "model/wofsstormcal.py",
    "train_script": "scripts/train.py",
    "inference_script": "scripts/inference.py",
    "evaluation_script": "scripts/result.py",
    "synthetic_data_script": "scripts/fake_data.py"
  },
  "architecture": {
    "family": "elastic-net logistic regression with isotonic calibration",
    "input_shape": ["N", 113],
    "output_shape": ["N", 3],
    "feature_groups": {"amplitude": 30, "spatial": 76, "object_property": 7},
    "hazards": ["tornado", "hail", "wind"],
    "lead_groups": ["first_hour", "second_hour"]
  },
  "paper_model": {
    "families": ["random_forest", "xgboost", "elastic_net_logistic_regression"],
    "probability_calibration": "isotonic regression",
    "cross_validation_folds": 5
  },
  "forecast_metadata": {
    "ensemble_members": 18,
    "grid_spacing_km": 3,
    "forecast_window_minutes": 30,
    "forecast_interval_minutes": 5,
    "first_hour_start_minutes": [0, 60],
    "second_hour_start_minutes": [65, 120]
  },
  "data": {"protocol": "wofs_storm_object_113_v1", "format": "NPZ"},
  "configuration_sources": [
    "conf/config.yaml",
    "model/wofsstormcal.py",
    "scripts/fake_data.py",
    "scripts/train.py",
    "scripts/inference.py",
    "scripts/result.py"
  ]
}